Decoupling the equations of regularized tomography

Deferring discretization can occasionally change our perspective on imaging problems. To illustrate, we offer a reformulation of regularized computed tomography (CT) in which the large system of coupled equations for the unknown smoothed image is decoupled into many smaller and simpler equations, each for a separate projection. Regularized CT thus becomes a two-stage process of (nonhomogeneous) smoothing of the projections followed by filtered backprojection. As a by-product, the repeated forward and backprojections common in iterative image reconstruction are eliminated. Despite the computational simplification, we demonstrate that this method can be used to reduce metal artifacts in X-ray CT images. The decoupling of the equations results from postponing the discretization of image derivatives that realize the smoothness constraint, allowing for this constraint to be analytically "transferred" from the image domain to the projection, or Radon, domain. Our analysis thus clarifies the role of image smoothness: it is an entirely intra-projection constraint.

[1]  Victor J. Sank,et al.  IMAGE RECONSTRUCTION FROM PROJECTIONS: ***I , 1978 .

[2]  Ken D. Sauer,et al.  A local update strategy for iterative reconstruction from projections , 1993, IEEE Trans. Signal Process..

[3]  Patrick Dupont,et al.  Reduction of metal streak artifacts in X-ray computed tomography using a transmission maximum a posteriori algorithm , 1999 .

[4]  E U Mumcuoğlu,et al.  Bayesian reconstruction of PET images: methodology and performance analysis. , 1996, Physics in medicine and biology.

[5]  Tsuneo Saito,et al.  Sinogram recovery with the method of convex projections for limited-data reconstruction in computed tomography , 1991 .

[6]  Alvaro R. De Pierro,et al.  A row-action alternative to the EM algorithm for maximizing likelihood in emission tomography , 1996, IEEE Trans. Medical Imaging.

[7]  J. Hsieh Adaptive streak artifact reduction in computed tomography resulting from excessive x-ray photon noise. , 1998, Medical physics.

[8]  Jeffrey A. Fessler,et al.  Grouped-coordinate ascent algorithms for penalized-likelihood transmission image reconstruction , 1997, IEEE Transactions on Medical Imaging.

[9]  M W Vannier,et al.  Fast iterative algorithm for metal artifact reduction in X-ray CT. , 2000, Academic radiology.

[10]  S. Helgason The Radon Transform , 1980 .

[11]  F. Natterer The Mathematics of Computerized Tomography , 1986 .

[12]  Jeffrey A. Fessler,et al.  Conjugate-gradient preconditioning methods for shift-variant PET image reconstruction , 1999, IEEE Trans. Image Process..